Optimization of fMRI methods to determine laterality of cortical activation during ankle movements of children with unilateral cerebral palsy
Bibliographic record
Abstract
Measurement of laterality of motor cortical activations may provide valuable information about lower limb control in children with unilateral cerebral palsy (UCP). Evidence from upper limb research suggests that increased contralateral activity may accompany functional gains. However, lower limb areas of activation and associated changes have been underexplored due to challenges with imaging motor cortical leg representations. In this study, methods for a task-based functional magnetic resonance imaging (fMRI) ankle dorsiflexion paradigm were refined with three pilot groups of participants: (i) adults (n = 5); (ii) typically developing (TD) children (n = 5) and; (iii) children with UCP (n = 4). Parameters of experimental design, task resistance, reproducibility, and pre-scan procedures were tested/refined using a staged development approach with additions or changes introduced if image quality did not meet pre-defined standards. When image quality was acceptable for two consecutive participants, the next participant group was recruited to test/refine the next parameter. The final paradigm involved an event-related design of a single dorsiflexion movement against individualized resistance, with two runs per leg. It included a pre-scan session to increase child comfort and determine task resistance. This paradigm produced valid data for laterality index (LI) calculations to determine the ratio of activity in each hemisphere. Ventricle and lesion masks were used in non-linear image registration, and individual thresholds were used for extent-based LI calculations. LI of dominant ankle movements were contralateral (LI ≥ +0.2) for TD children (mean LI = +0.89, std = 0.27) and children with UCP (mean LI = +0.86, std = 0.26). For the affected ankle of children with UCP, LI values indicated ipsilateral and/or contralateral activation (mean LI = +0.02, std = 0.71, range -0.92 to +1.00). This fMRI paradigm will support investigations of cortical activation and mechanisms of skill improvement following lower limb interventions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".